import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase__  =					get_tests_dir('''fixtures/test_sentencepiece.model''')
lowerCamelCase__  =					get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')

lowerCamelCase__  =					'''pt''' if is_torch_available() else '''tf'''




@require_sentencepiece
@require_tokenizers
class 					_UpperCAmelCase			(     lowerCAmelCase,			unittest.TestCase  ):



 '''simple docstring'''




 __A			       =					CamembertTokenizer
 __A			       =					CamembertTokenizerFast
 __A			       =					True
 __A			       =					True







 def 		__UpperCAmelCase				(		self				:   Optional[Any])						->	int:


   """simple docstring"""







   super().setUp()

   # We have a SentencePiece fixture for testing
   _UpperCamelCase           =    CamembertTokenizer(lowercase_)
   tokenizer.save_pretrained(self.tmpdirname)







 def 		__UpperCAmelCase				(		self				:   List[str])						->	Any:


   """simple docstring"""







   _UpperCamelCase           =    "<pad>"
   _UpperCamelCase           =    1

   self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase_)							, lowercase_)
   self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase_)							, lowercase_)







 def 		__UpperCAmelCase				(		self				:   Optional[Any])						->	Optional[Any]:


   """simple docstring"""







   _UpperCamelCase           =    list(self.get_tokenizer().get_vocab().keys())

   self.assertEqual(vocab_keys[0]							, "<s>NOTUSED")
   self.assertEqual(vocab_keys[1]							, "<pad>")
   self.assertEqual(vocab_keys[-1]							, "<mask>")
   self.assertEqual(len(lowercase_)							, 1004)







 def 		__UpperCAmelCase				(		self				:   Optional[int])						->	Optional[int]:


   """simple docstring"""







   self.assertEqual(self.get_tokenizer().vocab_size							, 1005)







 def 		__UpperCAmelCase				(		self				:   List[str])						->	List[str]:


   """simple docstring"""







   _UpperCamelCase           =    CamembertTokenizer(lowercase_)
   tokenizer.save_pretrained(self.tmpdirname)
   _UpperCamelCase           =    CamembertTokenizerFast.from_pretrained(self.tmpdirname)

   _UpperCamelCase           =    "I was born in 92000, and this is falsé."

   _UpperCamelCase           =    tokenizer.encode(lowercase_)
   _UpperCamelCase           =    rust_tokenizer.encode(lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)

   _UpperCamelCase           =    tokenizer.encode(lowercase_							, add_special_tokens=lowercase_)
   _UpperCamelCase           =    rust_tokenizer.encode(lowercase_							, add_special_tokens=lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)

   # <unk> tokens are not the same for `rust` than for `slow`.
   # Because spm gives back raw token instead of `unk` in EncodeAsPieces
   # tokens = tokenizer.tokenize(sequence)
   _UpperCamelCase           =    tokenizer.convert_ids_to_tokens(lowercase_)
   _UpperCamelCase           =    rust_tokenizer.tokenize(lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)







 def 		__UpperCAmelCase				(		self				:   Union[str, Any])						->	str:


   """simple docstring"""







   if not self.test_rust_tokenizer:
     return

   _UpperCamelCase           =    self.get_tokenizer()
   _UpperCamelCase           =    self.get_rust_tokenizer()

   _UpperCamelCase           =    "I was born in 92000, and this is falsé."

   _UpperCamelCase           =    tokenizer.tokenize(lowercase_)
   _UpperCamelCase           =    rust_tokenizer.tokenize(lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)

   _UpperCamelCase           =    tokenizer.encode(lowercase_							, add_special_tokens=lowercase_)
   _UpperCamelCase           =    rust_tokenizer.encode(lowercase_							, add_special_tokens=lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)

   _UpperCamelCase           =    self.get_rust_tokenizer()
   _UpperCamelCase           =    tokenizer.encode(lowercase_)
   _UpperCamelCase           =    rust_tokenizer.encode(lowercase_)
   self.assertListEqual(lowercase_							, lowercase_)







 @slow
 def 		__UpperCAmelCase				(		self				:   int)						->	int:


   """simple docstring"""







   _UpperCamelCase           =    {"input_ids": [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
   # fmt: on

   # camembert is a french model. So we also use french texts.
   _UpperCamelCase           =    [
       "Le transformeur est un modèle d'apprentissage profond introduit en 2017, "
       "utilisé principalement dans le domaine du traitement automatique des langues (TAL).",
       "À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus "
       "pour gérer des données séquentielles, telles que le langage naturel, pour des tâches "
       "telles que la traduction et la synthèse de texte.",
   ]

   self.tokenizer_integration_test_util(
       expected_encoding=lowercase_							, model_name="camembert-base"							, revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"							, sequences=lowercase_							, )





from __future__ import annotations

from collections import Counter
from random import random




class 					_UpperCAmelCase			:



 '''simple docstring'''




 def __init__(		self				:   List[str])						->	Any:


   """simple docstring"""







   _UpperCamelCase           =    {}







 def 		__UpperCAmelCase				(		self				:   Optional[Any]							, lowercase_				:   str)						->	None:


   """simple docstring"""







   _UpperCamelCase           =    {}







 def 		__UpperCAmelCase				(		self				:   List[str]							, lowercase_				:   str							, lowercase_				:   str							, lowercase_				:   float)						->	None:


   """simple docstring"""







   if nodea not in self.connections:
     self.add_node(lowercase_)
   if nodea not in self.connections:
     self.add_node(lowercase_)
   _UpperCamelCase           =    probability







 def 		__UpperCAmelCase				(		self				:   Any)						->	list[str]:


   """simple docstring"""







   return list(self.connections)







 def 		__UpperCAmelCase				(		self				:   Tuple							, lowercase_				:   str)						->	str:


   """simple docstring"""







   _UpperCamelCase           =    0
   _UpperCamelCase           =    random()

   for dest in self.connections[node]:
     current_probability += self.connections[node][dest]
     if current_probability > random_value:
       return dest
   return ""


def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__ )      ->dict[str, int]:




  '''simple docstring'''

  _UpperCamelCase           =    MarkovChainGraphUndirectedUnweighted()

  for nodea, nodea, probability in transitions:
    graph.add_transition_probability(a__    ,     a__    ,     a__ )

  _UpperCamelCase           =    Counter(graph.get_nodes() )
  _UpperCamelCase           =    start

  for _ in range(a__ ):
    _UpperCamelCase           =    graph.transition(a__ )
    visited[node] += 1

  return visited


if __name__ == "__main__":
   import doctest

   doctest.testmod()




